OAP read parquet

spark2.1

FileScanRDD
private def nextIterator(): Boolean = {
...
currentIterator = readFunction(currentFile)
...
}
OptimizedParquetFileFormat
override def buildReaderWithPartitionValues(
      sparkSession: SparkSession,
      dataSchema: StructType,
      partitionSchema: StructType,
      requiredSchema: StructType,
      filters: Seq[Filter],
      options: Map[String, String],
      hadoopConf: Configuration): PartitionedFile => Iterator[InternalRow] = {
      ...
      val reader = new OapDataReaderV1(file.filePath, m, partitionSchema, requiredSchema,
        filterScanners, requiredIds, pushed, oapMetrics, conf, enableVectorizedReader, options,
        filters, context)
      reader.read(file)
      ...
      }
OapDataReaderWriter.scala
override def read(file: PartitionedFile): Iterator[InternalRow] =
{
...
val iter = initialize()
...
}
def fullScan: OapCompletionIterator[Any] = {
      val start = if (log.isDebugEnabled) System.currentTimeMillis else 0
      //initialize  goto here
      val iter = fileScanner.iterator(requiredIds, filters)
      val end = if (log.isDebugEnabled) System.currentTimeMillis else 0

      _totalRows = fileScanner.totalRows()

      logDebug("Construct File Iterator: " + (end - start) + " ms")
      iter
    }
ParquetDataFile
def iterator(
    requiredIds: Array[Int],
    filters: Seq[Filter] = Nil): OapCompletionIterator[Any] = {
    val iterator = context match {
      case Some(c) =>
        // Parquet RowGroupCount can more than Int.MaxValue,
        // in that sence we should not cache data in memory
        // and rollback to read this rowgroup from file directly.
        if (parquetDataCacheEnable &&
          !meta.footer.getBlocks.asScala.exists(_.getRowCount > Int.MaxValue)) {
          addRequestSchemaToConf(configuration, requiredIds)
          //goto here
          initCacheReader(requiredIds, c,
            new VectorizedCacheReader(configuration,
              meta.footer.toParquetMetadata(), this, requiredIds))
        } else {
          addRequestSchemaToConf(configuration, requiredIds)
          initVectorizedReader(c,
            new VectorizedOapRecordReader(file, configuration, meta.footer))
        }
      case _ =>
        addRequestSchemaToConf(configuration, requiredIds)
        initRecordReader(
          new MrOapRecordReader[UnsafeRow](new ParquetReadSupportWrapper,
            file, configuration, meta.footer))
    }
    iterator.asInstanceOf[OapCompletionIterator[Any]]
  }

VectorizedCacheReader.scala
protected def initializeMetas(): Unit = {
    this.fileSchema = footer.getFileMetaData.getSchema
    val fileMetadata = footer.getFileMetaData.getKeyValueMetaData
    // init go to here
    val readContext = new ParquetReadSupportWrapper()
      .init(new InitContext(configuration, Collections3.toSetMultiMap(fileMetadata), fileSchema))
    this.requestedSchema = readContext.getRequestedSchema
    val sparkRequestedSchemaString =
      configuration.get(ParquetReadSupportWrapper.SPARK_ROW_REQUESTED_SCHEMA)
    this.sparkSchema = StructType.fromString(sparkRequestedSchemaString)
    val rowGroupMetas = footer.getBlocks.asScala
    this.rowGroupMetaIter = rowGroupMetas.iterator
    for (block <- rowGroupMetas) {
      this.totalRowCount += block.getRowCount
    }
  }
ParquetReadSupportWrapper.scala
override def init(context: InitContext): ReadContext = {
    readSupport.init(context)
  }
ParquetReadSupport.scala
override def init(context: InitContext): ReadContext = {
...
val parquetRequestedSchema =
      ParquetReadSupport.clipParquetSchema(context.getFileSchema, catalystRequestedSchema)
...
}

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转载自blog.csdn.net/zhixingheyi_tian/article/details/84971402
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